Skip to main content
Powered by ShareScore

Find research datasets worth reusing

Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.

10,553

datasets available to search

ShareScore release 0.7.1

Reset

Dataset results

10,553 results for “measurements”

Learn how ShareScore rates datasets ↗
zenodo44/100

FT10 Bonaccorsi 7-key fagottino: measurements, photos, endoscopic video

<p>Dataset of FT10&nbsp;&nbsp;Bonaccorsi&nbsp;7-key fagottino&nbsp;containing detailed external and internal measurements, photos, and an endoscopic video. &nbsp;</p> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Apr 2019View details →
zenodo44/100

FT11 Cahusac (1) 6-key tenoroon: measurements, photos, endoscopic video

<p>&nbsp;Dataset of FT11&nbsp;Cahusac 6-key tenoroon containing detailed external and internal measurements, photos, and an endoscopic video. &nbsp;</p>

opencc-by-4.0Apr 2019View details →
zenodo44/100

FT19 Merklein 8-key tenoroon: measurements, photos, endoscopic video

<p>Dataset of FT19 Merklein 8-key tenoroon containing detailed external and internal measurements, photos, and an endoscopic video.</p>

opencc-by-4.0Mar 2019View details →
zenodo44/100

FT34 Tuerlinckx (2) 5-key tenoroon: measurements, photos, endoscopic video

<p>Dataset of FT34&nbsp;Tuerlinckx 5-key tenoroon&nbsp;containing detailed external and internal&nbsp;measurements, photos, and an endoscopic video. &nbsp;</p>

opencc-by-4.0Mar 2019View details →
zenodo44/100

FT20 Müller 4-key fagottino: measurements, photos, endoscopic video

<p>Dataset of F20 M&uuml;ller 4-key fagottino containing detailed external and internal&nbsp;measurements, photos, and an endoscopic video</p>

opencc-by-4.0Mar 2019View details →
zenodo44/100

FT22 Proff 5-key tenoroon: measurements, photos, endoscopic video

<p>Dataset of FT22 Proff 5-key tenoroon containing&nbsp;detailed external and internal measurements, photos, and an endoscopic video. &nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Jun 2019View details →
zenodo44/100

Measurements of Ice Nucleating Particles in Beijing, China - Data and processing code

<p>Dataset needed to replicate findings published in the journal article &quot;Measurements of Ice Nucleating Particles in Beijing, China, published in the Journal of Geophysical Research. The dataset contains the following:</p> <p>1. Data files containing raw data from a Continuous Flow Diffusion Chamber - Ice Activation Spectrometer (CFDC-IAS), in comma-delimited format).</p> <p>2. Data and processing files for analysis of backward air trajectories as an Igor Pro 8 packed experiment package file. Igor Pro is available from www.wavemetrics.com and a free 30-day trial version can be used to export data to other formats.</p> <p>3. Data and processing files for analysis of CFDC, APS and meteorological data, including data in the form of waves, as part of an Igor Pro 8 packed experiment package.</p>

opencc-by-4.0Dec 2018View details →
zenodo44/100

MOSIDEO: Sea ice properties and oil concentrations measured during the HSVA experiment during MOSIDEO

<p>Physical ice properties (porosity, permeability and brine volume fraction), and oil concentration measured on collected ice cores during the experiments.</p> <ul> <li>Oil concentrations are measured using a UV-fluorescence meter TD500TM (Turner Designs Hydrocarbon Instruments, Inc.)</li> <li>Ice temperature measured in-situ with thermocouple strings</li> <li>Porosity and permeability fields are computed from ice and temperature profiles using semi-empirical equations (Cox and Weeks, 1983; Golden et al., 2009). The oil intake and pore space saturation in oil (oil saturation) are derived from acoustic data of the oil/water and oil/ice interface position.</li> </ul>

opencc-by-4.0Jul 2019View details →
zenodo44/100

Dataset for "Gross primary productivity of four European ecosystems constrained by joint CO2 and COS flux measurements"

<p>Data of measurements and model output of the publication &quot;Gross primary productivity of four European ecosystems constrained by joint CO<sub>2</sub> and COS flux measurements&quot;.</p> <p>Data consists of micrometeorological data, COS and CO<sub>2</sub> flux measurements for 4 sites including filters for the fluxes.</p> <p>The sites include: a managed temperate mountain grassland in Austria (18.06.-21.08.2015), a Mediterranean savanna ecosystem in Spain(29.04.-24.05.2016)), a Temperate beach forest in Denmark(07.06.-03.07.2016) and an agricultural soy bean field in Italy(03.07.-01.08.2017).</p> <p>Version 2: param2950** are now correct (were filled with the same values for all field sites) &nbsp;</p> <p>For additional information&nbsp;please contact:&nbsp;<a href="mailto:Georg.Wohlfahrt@uibk.ac.at">Georg.Wohlfahrt@uibk.ac.at</a></p>

opencc-by-4.0Feb 2019View details →
zenodo44/100

Absolute frequency measurement of the 1 S 0 – 3 P 0 transition of 171 Yb with a link to International Atomic Time

<p>Dataset of the INRIM Yb clock measured respect to TAI collected between October 2018 to February 2019.<br> &nbsp;</p> <p>YbvsSIm-viaEAL.dat: montly data with columns</p> <pre><code>MJDstart: start date in MJD MJDstop: stop date in MJD MJDmed: mid point date in MJD MJDbaro: baricenter date in MJD Ybduty: Yb clock duty time y0=Yb/HM3: ratio between Yb clock and H Maser 03 u0: statistical uncertainty of y0 uB0: systematic uncertainty of y0 y1=extrap.: extrapolation over HM3 udead1: uncertainty of y1 from dead times udrift1: uncertainty of y1 from HM3 drift HM3drift/d: HM3 drift per day udrift/d: uncertainty of HM3 drift y2=HM3/UTCit: ratio between HM3 and UTC(IT) u2: uncertainty of y2 y3=UTCit/TAI: ratio between UTC(IT) and TAI u3: uncertainty of y3 y4=EALext.: extrapolation over EAL udead4: uncertainty of y4 from dead times udrift4: uncertainty of y4 from EAL drift y5=-d: ratio between TAI and the SI second from Circular T u5: uncertainty of y5 uA5: statistical uncertainty of y5 uB5: systematic uncertainty of y5 y=Yb/SI: final ratio beween the Yb clock and the Si second uA: not used uB: not used u: uncertainty of y </code></pre> <p>YbvsTAId.dat: data every 5 days with columns:</p> <pre><code>MJDstart: start date in MJD MJDstop: stop date in MJD MJDmed: mid point date in MJD MJDbaro: baricenter date in MJD Ybduty: Yb clock duty time y0=Yb/HM3: ratio between Yb clock and H Maser 03 u0: statistical uncertainty of y0 uB0: systematic uncertainty of y0 y1=extrap.: extrapolation over HM3 udead1: uncertainty of y1 from dead times udrift1: uncertainty of y1 from HM3 drift HM3drift/d: HM3 drift per day udrift/d: uncertainty of HM3 drift y2=HM3/UTCit: ratio between HM3 and UTC(IT) u2: uncertainty of y2 y3=UTCit/TAI: ratio between UTC(IT) and TAI u3: uncertainty of y3 y=Yb/TAI: final ratio beween the Yb clock and TAI uA: not used uB: not used u: uncertainty of y </code></pre> <p>&nbsp;</p>

opencc-by-4.0Sep 2019View details →
zenodo44/100

Doppler lidar datasets of UDINE measurement campaign at TROPOS Leipzig, Germany

<p>The Doppler lidar dataset of the Up- and Downdraft in Drop and Ice Nucleation Experiment (UDINE, 2010-2013) is published. This dataset is part of the publication B&uuml;hl et al., &quot;Impact of vertical air motions on ice formation rate in mixed-phase cloud layers&quot;, NPJ Climate and Atmospheric Science, 2019.</p> <p>Time-height resolved measurements of mean vertical Doppler velocity of aerosol and cloud particles over the measurement site. Most data is recorded in vertical stare with 2s measurement time. Files are in NetCDF-format and contain the following variables:</p> <p>amp(time,height): The signal strength (SNR) recorded by the data acquisition.<br> data(time,height): The first moment of the main peak in the Doppler spectrum<br> heightresolution: The resolution of the data acquisition in nanoseconds<br> measurement_time(time,datetime): Time of recording in human readable format [YYYYMMDD,hhmmss]<br> scanposition(time,scanposition): Two element array with position of the scanner in [azimuth,off-zenith-angle]<br> shots(time): The number of shots used for averaging. Spectra are averaged at a rate of 750 shots/s so this variables indicates if the system has functioned nominally.</p>

opencc-by-4.0Sep 2019View details →
zenodo44/100

Water temperature measurements collected during austral summer 2017/2018 on lakes located in the Schirmacher oasis, East Antarctica.

<p>Lakes&rsquo; water temperature are measured on lakes of three types (epiglacial, epishelf and land-locked) located in the Schirmacher oasis, East Antarctica. The temporal hydrological network is equipped by 11 temperature sensors, which are measured both surface and bottom water temperature of lakes. The surface temperature is recorded with the temperature loggers iButton DS1922L/DS1922T (https://www.maximintegrated.com/en/datasheet/index.mvp/id/4088) on 8 lakes. The sensors are deployed within a distance of 1&ndash;3 m from a lake&rsquo;s coast, on a depth of 0.02 m. The lake&rsquo;s surface temperature is also measured on two lakes with the temperature sensors by HOBO Water Level U20L (https://www.onsetcomp.com/products/data-loggers/u20l-01), which are deployed on the depth of 0.2 m. One HOBO sensor is installed to be attached to a lake&rsquo;s ground on a depth approximately 0.5 m. The measurements cover the period of over 12&ndash;36 days depending on a lake. The data set includes the field campaign&rsquo;s report of 63 RAE in the Schirmacher oasis (a text, in Russian) as a pdf-file, the metadata for the measurements (name, elevation, lon/lat of the temperature sensors deployed; name of the lakes; period with measurements; comments) as a shp-file, and the tables with water temperature measured for each lakes (as files of CSV format). Also, the deployment of the temperature sensor on the Lake Pomornik is presented in the jpg-file.</p> <p>&nbsp;</p>

opencc-by-4.0Sep 2019View details →
zenodo44/100

Festival of Frequency Measurement 1 October 2019 for WWV 5 MHz - Toby Haynes VE7CNF

<p>Festival of Frequency Measurement 1 October 2019 for WWV 5 MHz</p> <p>Toby Haynes VE7CNF<br> Location:&nbsp; &nbsp; 49.266918N &nbsp; 122.900887W &nbsp; Grid CN89ng&nbsp; &nbsp;Burnaby, BC, Canada<br> Start Time:&nbsp; 2019 Sept 30 at 23:58 UTC<br> End time:&nbsp; &nbsp; 2019 &nbsp;Oct &nbsp;2 at 00:02 UTC<br> Antenna:&nbsp; &nbsp; &nbsp;&quot;Inverted L&quot; vertical with ICOM AH-4 auto tuner, 50 ft high, 70 ft horizontal top wire.<br> Receiver:&nbsp; &nbsp; ICOM IC-7410 with internal TCXO reference and internal USB sound card chip with separate clock crystal.<br> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; Receiver in USB mode with carrier frequency 4998.5 kHz to give a 1500 Hz audio tone for the WWV 5 MHz carrier.<br> Measurement:&nbsp; 1500 Hz tone frequency estimated using program FLDigi v4.1.08 in frequency analysis mode.</p> <p>There was a drop in the WWV 5 MHz signal level around 15:00 UTC, after which the reduced SNR caused more variation in the FLDigi frequency measurements.</p> <p>Frequency calibration:</p> <p>Before and after the data set, the receiver frequency error was determined by using the receiver and FLDigi to measure a reference 5 MHz sine wave from a Rigol&nbsp;DG1032 function generator with external 10 MHz GPS-disciplined frequency reference (Trimble).<br> The &quot;VE7CNF raw_2019-09-30-1810 UTC.csv&quot; file includes the reference measurements and the data set.</p> <p>The two reference signal measurements were:<br> &nbsp; &nbsp;Receiver frequency error +0.066 Hz averaged for 1 minute starting 2019 Sept 30 at 18:10:25 UTC&nbsp;<br> &nbsp; &nbsp;Receiver frequency error +0.028 Hz averaged for 1 minute starting 2019 &nbsp;Oct &nbsp;2 at 00:03:10 UTC</p> <p>Receiver frequency error at each time during the data set was then estimated, assuming that the error changed linearly over time betwen the two reference&nbsp;measurements. The estimated receiver frequency errors were applied to correct the data set in &quot;VE7CNF CN89ng 5 MHz_2019-09-30-2358 UTC.csv.&quot;</p> <p>The measured WWV 5 MHz frequency error vs time is graphed in &quot;VE7CNF_WWV5MHz_2019-10-01UTC.JPG,&quot; with a moving 1-minute average applied to the frequency error.&nbsp;The frequency dropped around 01:30 (local sunset was 01:51 UTC) and increased around 14:00 (local sunrise was 14:13 UTC).<br> <br> &nbsp;</p>

opencc-by-4.0Oct 2019View details →
zenodo44/100

3D wind speed and CO2/H20 concentration measurements collected during austral summer 2017/2018 over an ice free surface of a shallow lake located in the Schirmacher oasis, East Antarctica.

<p>The data set includes measurements collected by the integrated CO2 and H2O open-path gas analyzer and 3-D sonic anemometer (Irgason by Campbell Scientific with serial number 1243, https://www.campbellsci.com/irgason).&nbsp; The instrument was operated from 01.01.2018 to 07.02.2018. It was deployed on the north-west shore of the Lake Zub/Priyadarshini (S70&deg; 45&prime; 41.5&Prime;, E011&deg; 44&prime; 16.6&Prime;) on the distance of 10 m from the coast. The instrument was placed on the aluminum tripod on the height of 2 m, and directed to south-eastwards (137 SE).&nbsp; Six metal guidelines were linked to anchors, and the boom was fixed on the tripod. Two rechargeable batteries (12V/33Ah) were used in additional to two solar panels to power supply of the instrument (irgason_deployment.jpg). The format of the output files is given in Irgason_output.pdf.&nbsp; The raw data are packed into the *.dat files (one per day) and then compressed (bz2). The calibration of the Irgason was done 21.08.2017 in the lab of the Finnish Meteorological Institute with standard zero-and-span procedure, and then the instrument is adjusted accordingly.</p>

opencc-by-4.0Dec 2018View details →
zenodo44/100

Intermittency in wind-driven surface alteration on Mars interpreted from wind streaks and measurements by InSight

<p>Shapefiles associated with the GRL publication:&nbsp;Intermittency in wind-driven surface alteration on Mars interpreted from wind streaks and measurements by InSight</p>

opencc-by-4.0Oct 2019View details →
zenodo44/100

Empirical measurements of function placements and executions in a mixed cloud-edge cluster

<p>Empirical measurements used for the Skippy Scheduler, an optimized container scheduler for serverless edge computing in Kubernetes.</p>

opencc-by-4.0Nov 2019View details →
zenodo44/100

Surface deformation of the Mw 6.4 and Mw 7.1 Ridgecrest earthquakes measured from subpixel correlation of Copernicus Sentinel-2 optical images

<p>Surface deformation of the Mw 6.4 and Mw 7.1 Ridgecrest earthquakes measured from subpixel correlation of Copernicus Sentinel-2 optical images&nbsp;</p>

opencc-by-4.0Nov 2019View details →
zenodo44/100

Validation of Emission Spectroscopy Gas Temperature Measurements Using a Standard Flame Traceable to the International Temperature Scale of 1990 (ITS-90)

<p>Data underpinning the associated publication (https://doi.org/10.1007/s10765-019-2557-6) on accurate traceable measurement of post-flame temperatures.</p>

opencc-by-4.0Nov 2019View details →
zenodo44/100

3D displacement field and fault-offset measurements for the northern Kaikōura ruptures

<p>Contents:</p> <p>1. East, north and vertical components of the co-seismic displacement field for three faults (the Kekerengu, Jordan and Upper Kowhai faults) that ruptured in the 2016 Kaikoura earthquake, New Zealand (east.tif, north.tif, vertical.tif).</p> <p>2. Shapefiles containing&nbsp;offsets across the faults of interest, measured from the displacement field (shapefiles.zip).</p> <p>3. CSV files&nbsp;containing&nbsp;offsets across the faults of interest, measured from the displacement field (csvs.zip).&nbsp;</p> <p>Our methodology is described in the following manuscript:</p> <p>Howell et al., 2019.&nbsp;3D surface displacements during the 2016 MW 7.8 Kaikōura earthquake (New Zealand) from photogrammetry-derived point clouds, Journal of Geophysical Research Solid Earth, submitted.</p>

opencc-by-4.0Dec 2019View details →
zenodo44/100

Phantom measurement data for 'Fast bias-corrected conductivity mapping using stimulated echoes', Iyyakkunnel et al. (2024)

<p>This dataset contains the phantom measurement data used in the article by Iyyakkunnel et al., titled "Fast Bias-Corrected Conductivity Mapping Using Stimulated Echoes," published in MAGMA, 2024 (doi: 10.1007/s10334-024-01194-3). In this study, the feasibility of using a stimulated echo sequence for electrical properties tomography (EPT) is demonstrated. The data were acquired with a 3T MRI system (Magnetom Prisma; Siemens Healthcare, Erlangen, Germany) using a dual-tuned 1H/23Na quadrature head coil for transmission and reception (Rapid Biomedical, Rimpar, Germany).<br>The dataset includes magnitude and phase measurements for the proposed Double-Angle Stimulated Echo (DA-STE) sequence, as well as reference measurements, including Double Angle measurements using a Gradient Echo sequence (GRE-DAM) for the B1+ magnitude, and a Single Echo Spin Echo sequence (SE) for the transceive phase.<br>For both the DA-STE and SE sequences, each measurement was repeated with inverted readout gradient polarities, denoted as LR (left-right) and RL (right-left) in the respective measurement folders. For each measurement, magnitude and phase data are provided in separate folders (in dicom (.dcm) format). Please note that for DA-STE, the two echo acquisitions are sequentially stored in the same measurement folder.<br>For further measurement details, please refer to the mentioned original article.</p>

opencc-by-4.0Aug 2024View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated datasets

Allen Brain Atlas

Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record